论文标题
使用圆形密度的叶子聚类
Leaf clustering using circular densities
论文作者
论文摘要
在植物学的生物学领域，叶状识别是一项重要任务。表征叶状的一种方法是通过质心轮廓距离（CCD）。每个CCD路径可能具有不同的分辨率，因此可以通过考虑圆形密度来进行归一化。通过减去平均优选方向旋转密度。密度之间的距离度量用于产生分层聚类方法以对叶子进行分类。我们使用真实数据集说明了我们的方法。
In the biology field of botany, leaf shape recognition is an important task. One way of characterising the leaf shape is through the centroid contour distances (CCD). Each CCD path might have different resolution, so normalisation is done by considering that they are circular densities. Densities are rotated by subtracting the mean preferred direction. Distance measures between densities are used to produce a hierarchical clustering method to classify the leaves. We illustrate our approach with a real dataset.
